Linear Regression Assumptions All variables are continuous numeric, not categorical Data is free of missing values and outliers There's a linear relationship between predictors and predictant All predictors are independent of each other Residuals(or prediction errors) are normally distributed importnumpyas...
dataset=pd.read_csv('/Users/xiehao/Desktop/100-Days-Of-ML-Code-master/datasets/studentscores.csv')X=dataset.iloc[:,:1].valuesY=dataset.iloc[:,1].values X_train,X_test,Y_train,Y_test=train_test_split(X,Y,test_size=1/4,random_state=0)regressor=LinearRegression()regressor=regressor.fi...
Python Copy model = LinearRegression(fit_intercept=True) X = df['ppgdp'][:, np.newaxis] y = df['lifeExpF'] model.fit(X, y) x_plot = np.linspace(0, 100000, 1000) y_plot = model.predict(x_plot[:, np.newaxis]) plt.scatter(df['ppgdp'], df['lifeExpF'], alpha=0.3) ...
# Fitting Simple LinearRegression to the training setfromsklearn.linear_modelimportLinearRegression regressor = LinearRegression() regressor.fit(X_train,y_train)# 通过train集找到曲线# 对测试集进行预测y_pred = regressor.predict(X_test)# visualising the Traning set resultsplt.scatter(X_train, y_tra...
Breadcrumbs simple-linear-regression-notebook / linear-regression-demo.ipynb Latest commit Philipp Bauch Delete python script for linear model 53a5081· Jun 7, 2017 HistoryHistory File metadata and controls Preview Code Blame 304 lines (304 loc) · 46.4 KB Raw Viewer requires iframe....
big-datasimpletensorflowlinear-regressiondistributed-computingtensorflow-tutorialstensorflow-exercisestensorflow-examples UpdatedMar 14, 2017 Python azhon/AppUpdate Star2.3k Code Issues Pull requests Android App update library. Android版本更新库,简单、轻量、可随意定制 ...
(input_size = emb_size, hidden_size = hidden_size) # 全连接层 self.fc = paddle.nn.Linear(in_features = hidden_size, out_features = 2) # Softmax层 self.softmax = paddle.nn.Softmax() # 网络的前向计算函数 def forward(self, x): print("Emb前:", x) x = self.emb(x) print("...
We present a fast and simple algorithm for super-resolution with single images. It is based on penalized least squares regression and exploits the tensor structure of two-dimensional convolution. A ridge penalty and a difference penalty are combined; the
Pu7aDTNVXTTpcg#Youku video tutorial: http://i.youku.com/pythontutorial"""Please note, this code is only for python 3+. If you are using python 2+, please modify the code accordingly."""from__future__importprint_functionfromsklearnimportdatasetsfromsklearn.linear_modelimportLinearRegression...
Input DATASETS linear-regression-dataset Language Python License This Notebook has been released under the Apache 2.0 open source license. Continue exploring Input1 file arrow_right_alt Output0 files arrow_right_alt Logs4.1 second run - successful arrow_right_alt Comments1 comment arrow_right_alt...